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Modeling solar power plant electricity supply chain toward renewable energy consumption
Pub Date : 2025-01-18 DOI: 10.1016/j.prime.2025.100907
Mohammad Reza Eslami Rasekh , Farzad Mohammad Sharifi , Somaieh Alavi , Nassibeh Janatyan
This paper aims to introduce a model of the solar plant electricity supply chain, encompassing mixed power plants, transmission lines, and consumers, with a focus on optimization and consideration of uncertainties. Within this article, the supply chain of solar power plants is delineated based on various parameters. The quantities of power plants and solar panels are determined by different priorities, such as investment levels, pollution mitigation, and reduction of gas consumption by conventional power plants, utilizing the particle swarm algorithm for optimal outcomes. The proposed model addresses uncertainties related to electricity demand, solar radiation levels, and consequently, the power production of solar panels, through the application of type 2 fuzzy logic. The optimization of the model is done keeping in mind various constraints including the supply of electricity and the maximum allowed use of solar cells. The innovation of this article is in the design of the supply chain model from the point of view of the uncertainty of electric power production and the amount of consumer demand and the optimal selection of solar panels for solar power plants to minimize the electricity consumption of the gas power plant and the amount of pollution caused by it. Based on the results obtained from the simulation of this article, it has been shown that considering the maximum investment capacity, up to 76 % of the electric energy can be supplied by building five solar power plants at certain distances from the electric substations around the case study. Considering the maximum weight coefficients for CO2 plant emissions and gas consumption, five solar power plants are the optimal number that is achieved by proposed algorithm. The power capacity of five solar power plants is optimized 4.100,4.222,3.920,4.375and 3.991MW, respectively. To evaluation of the proposed model, PSO algorithm is compared to GA and the results show that cost function and convergence time in PSO is less than GA in the various weight coefficients scenarios. This optimal mode leads to the maximum reduction of gas consumption in the gas power plant, and on the other hand, the amount of pollution is minimized. The prediction of this number of power plants with different priorities is presented in this article and different policies can be considered strategically for this model of the supply chain.
{"title":"Modeling solar power plant electricity supply chain toward renewable energy consumption","authors":"Mohammad Reza Eslami Rasekh ,&nbsp;Farzad Mohammad Sharifi ,&nbsp;Somaieh Alavi ,&nbsp;Nassibeh Janatyan","doi":"10.1016/j.prime.2025.100907","DOIUrl":"10.1016/j.prime.2025.100907","url":null,"abstract":"<div><div>This paper aims to introduce a model of the solar plant electricity supply chain, encompassing mixed power plants, transmission lines, and consumers, with a focus on optimization and consideration of uncertainties. Within this article, the supply chain of solar power plants is delineated based on various parameters. The quantities of power plants and solar panels are determined by different priorities, such as investment levels, pollution mitigation, and reduction of gas consumption by conventional power plants, utilizing the particle swarm algorithm for optimal outcomes. The proposed model addresses uncertainties related to electricity demand, solar radiation levels, and consequently, the power production of solar panels, through the application of type 2 fuzzy logic. The optimization of the model is done keeping in mind various constraints including the supply of electricity and the maximum allowed use of solar cells. The innovation of this article is in the design of the supply chain model from the point of view of the uncertainty of electric power production and the amount of consumer demand and the optimal selection of solar panels for solar power plants to minimize the electricity consumption of the gas power plant and the amount of pollution caused by it. Based on the results obtained from the simulation of this article, it has been shown that considering the maximum investment capacity, up to 76 % of the electric energy can be supplied by building five solar power plants at certain distances from the electric substations around the case study. Considering the maximum weight coefficients for CO<sub>2</sub> plant emissions and gas consumption, five solar power plants are the optimal number that is achieved by proposed algorithm. The power capacity of five solar power plants is optimized <span><math><mrow><mn>4.100</mn><mo>,</mo><mspace></mspace><mn>4.222</mn><mo>,</mo><mspace></mspace><mn>3.920</mn><mo>,</mo><mspace></mspace><mn>4.375</mn><mspace></mspace></mrow></math></span>and <span><math><mrow><mn>3.991</mn><mspace></mspace><mi>M</mi><mi>W</mi></mrow></math></span>, respectively. To evaluation of the proposed model, PSO algorithm is compared to GA and the results show that cost function and convergence time in PSO is less than GA in the various weight coefficients scenarios. This optimal mode leads to the maximum reduction of gas consumption in the gas power plant, and on the other hand, the amount of pollution is minimized. The prediction of this number of power plants with different priorities is presented in this article and different policies can be considered strategically for this model of the supply chain.</div></div>","PeriodicalId":100488,"journal":{"name":"e-Prime - Advances in Electrical Engineering, Electronics and Energy","volume":"11 ","pages":"Article 100907"},"PeriodicalIF":0.0,"publicationDate":"2025-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143178122","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A new hybrid distance and similarity based scenario reduction approach for stochastic economic operation of microgrid
Pub Date : 2025-01-16 DOI: 10.1016/j.prime.2025.100905
Gaurav Gangil, Amit Saraswat, Sunil Kumar Goyal
This paper attempts to develop a multi-time period stochastic optimization model for economic operations of a typical microgrid by employing a scenario-based analysis approach to exploit various uncertainties associated with variable renewable energy (VRE) generations, electricity prices, and load demand. This stochastic model is aimed at generating the optimum schedules for various dispatchable generating resources such as micro-turbines, fuel cells, utility grid, energy storage devices as per the availability of the various VRE resources to meet the uncertain demand for a day-to-day microgrid operation. Further, a suitable scenario reduction approach named hybrid distance and similarity (HDS) approach is proposed to cater for two diverse objectives i.e., minimization of the Manhattan distance and maximization of the similarity index between an optimal scenario pair for generating a reduced scenario set by eliminating large redundant scenarios from its original large set. To verify the effectiveness of the proposed HDS, its performance is compared with three well developed distinct methods such as SBR (simultaneous backward reduction method), FFS (fast forward selection method), and SIMCOR (similarity-correlation method) on two different stochastic optimization problems including one real-life economic microgrid problem. All the competing scenario reduction methods are compared in terms of various performance indices i.e. OSDI (Output Sample Deviation Index), PSRI (Percentage Scenario Reduction Index), objective values, and computation time to verify their suitability and effectiveness on complex optimization problems. The proposed HDS method is found to be capable in achieving the lowest OSDI value of 5.68 at 98 % scenario reduction while compared to other competing methods i.e. 12.95 by SBR, 14.76 by FFS, and 16.32 by SIMCOR for the real-life microgrid problem. Moreover, the proposed HDS methods also outperforms the other three competing methods in terms of their objective function values after 98 % scenario reduction with a least computation time burden i.e. 87.6 %, 1.11 %, and 53 % less computing times are needed by HDS, FFS, and SIMCOR, respectively. These comprehensive simulation results reveal that the proposed HDS method is capable to generate high-quality scenarios, better approximation, superior stability, and with lower computation time burden as compared to the other three competing scenario reduction approaches.
{"title":"A new hybrid distance and similarity based scenario reduction approach for stochastic economic operation of microgrid","authors":"Gaurav Gangil,&nbsp;Amit Saraswat,&nbsp;Sunil Kumar Goyal","doi":"10.1016/j.prime.2025.100905","DOIUrl":"10.1016/j.prime.2025.100905","url":null,"abstract":"<div><div>This paper attempts to develop a multi-time period stochastic optimization model for economic operations of a typical microgrid by employing a scenario-based analysis approach to exploit various uncertainties associated with variable renewable energy (VRE) generations, electricity prices, and load demand. This stochastic model is aimed at generating the optimum schedules for various dispatchable generating resources such as micro-turbines, fuel cells, utility grid, energy storage devices as per the availability of the various VRE resources to meet the uncertain demand for a day-to-day microgrid operation. Further, a suitable scenario reduction approach named hybrid distance and similarity (HDS) approach is proposed to cater for two diverse objectives i.e., minimization of the Manhattan distance and maximization of the similarity index between an optimal scenario pair for generating a reduced scenario set by eliminating large redundant scenarios from its original large set. To verify the effectiveness of the proposed HDS, its performance is compared with three well developed distinct methods such as SBR (simultaneous backward reduction method), FFS (fast forward selection method), and SIMCOR (similarity-correlation method) on two different stochastic optimization problems including one real-life economic microgrid problem. All the competing scenario reduction methods are compared in terms of various performance indices i.e. OSDI (Output Sample Deviation Index), PSRI (Percentage Scenario Reduction Index), objective values, and computation time to verify their suitability and effectiveness on complex optimization problems. The proposed HDS method is found to be capable in achieving the lowest OSDI value of 5.68 at 98 % scenario reduction while compared to other competing methods i.e. 12.95 by SBR, 14.76 by FFS, and 16.32 by SIMCOR for the real-life microgrid problem. Moreover, the proposed HDS methods also outperforms the other three competing methods in terms of their objective function values after 98 % scenario reduction with a least computation time burden i.e. 87.6 %, 1.11 %, and 53 % less computing times are needed by HDS, FFS, and SIMCOR, respectively. These comprehensive simulation results reveal that the proposed HDS method is capable to generate high-quality scenarios, better approximation, superior stability, and with lower computation time burden as compared to the other three competing scenario reduction approaches.</div></div>","PeriodicalId":100488,"journal":{"name":"e-Prime - Advances in Electrical Engineering, Electronics and Energy","volume":"11 ","pages":"Article 100905"},"PeriodicalIF":0.0,"publicationDate":"2025-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143178605","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Detection and classification of single-circuit and intra-circuit faults based on analysis of current signals of near-end terminal in double-circuit transmission lines
Pub Date : 2025-01-16 DOI: 10.1016/j.prime.2025.100904
Mahyar Abasi , Pirooz Gorjian
This paper presents a method of inter-circuit and intra-circuit fault detection in a double-circuit transmission line based on the analysis of six-phase current signals of a single terminal. The method is developed by analyzing the output results of several mathematical integral transforms, including the modified Stockwell, Hilbert, and modal transforms. The algorithm is designed in three steps. In the first step, by investigating the alpha component of the modal transform, it can be recognized that the fault is single-circuit or double-circuit. Then, in the second step, by analyzing the zero component of the modal transform, it can be identified if the fault is grounded or not. In the third step, by using the analysis of a new index based on the combination of modified Stockwell and Hilbert transforms and a statistical index based on correlation, the faulty phase of the double-circuit line can be identified. The method is coded in the MATLAB environment and the test network is modeled in MATLAB/Simulink. The implementation results of different fault scenarios as well as the analysis of the algorithm's behavior under critical conditions validates the algorithm's high performance.
{"title":"Detection and classification of single-circuit and intra-circuit faults based on analysis of current signals of near-end terminal in double-circuit transmission lines","authors":"Mahyar Abasi ,&nbsp;Pirooz Gorjian","doi":"10.1016/j.prime.2025.100904","DOIUrl":"10.1016/j.prime.2025.100904","url":null,"abstract":"<div><div>This paper presents a method of inter-circuit and intra-circuit fault detection in a double-circuit transmission line based on the analysis of six-phase current signals of a single terminal. The method is developed by analyzing the output results of several mathematical integral transforms, including the modified Stockwell, Hilbert, and modal transforms. The algorithm is designed in three steps. In the first step, by investigating the alpha component of the modal transform, it can be recognized that the fault is single-circuit or double-circuit. Then, in the second step, by analyzing the zero component of the modal transform, it can be identified if the fault is grounded or not. In the third step, by using the analysis of a new index based on the combination of modified Stockwell and Hilbert transforms and a statistical index based on correlation, the faulty phase of the double-circuit line can be identified. The method is coded in the MATLAB environment and the test network is modeled in MATLAB/Simulink. The implementation results of different fault scenarios as well as the analysis of the algorithm's behavior under critical conditions validates the algorithm's high performance.</div></div>","PeriodicalId":100488,"journal":{"name":"e-Prime - Advances in Electrical Engineering, Electronics and Energy","volume":"11 ","pages":"Article 100904"},"PeriodicalIF":0.0,"publicationDate":"2025-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143178120","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Performance analysis of a multi-user outdoor visible light communication system using wavelength division multiplexing (WDM) with RZ-OOK and NRZ-OOK modulations for V2X communications
Pub Date : 2025-01-16 DOI: 10.1016/j.prime.2025.100900
Anass Kharbouche, Hamza Ouamna, Zhour Madini, Younes Zouine
Vehicle-to-Everything (V2X) communication represents a revolution in traffic management and road safety, with innovation at the heart of this evolution. In this context, Visible Light Communication (VLC) emerges as a promising alternative to meet the demands for high-speed and low-latency communication. LED lamps, primarily used for lighting, can also serve as data transmission mediums. This article proposes a VLC system utilizing Wavelength Division Multiplexing (WDM) to simultaneously transmit data streams from different sources via a Free Space Optical (FSO) channel.
We evaluated the performance of this system by analyzing the impact of the Return to Zero (RZ) and Non Return to Zero (NRZ) formats at the optical transmitter on the WDM/FSO system. Simulations were conducted by varying the FSO channel distance and testing different throughput scenarios while considering weather conditions. The results show that Return to Zero, On-Off Keying (RZ-OOK) modulation can achieve high data rates at short distances, while Non Return to Zero, On-Off Keying (NRZ-OOK) modulation excels at longer distances with moderate data rates, particularly under adverse weather conditions.
These findings pave the way for innovative applications in the field of V2X communications, addressing the specific needs of both urban and non-urban environments.
{"title":"Performance analysis of a multi-user outdoor visible light communication system using wavelength division multiplexing (WDM) with RZ-OOK and NRZ-OOK modulations for V2X communications","authors":"Anass Kharbouche,&nbsp;Hamza Ouamna,&nbsp;Zhour Madini,&nbsp;Younes Zouine","doi":"10.1016/j.prime.2025.100900","DOIUrl":"10.1016/j.prime.2025.100900","url":null,"abstract":"<div><div>Vehicle-to-Everything (V2X) communication represents a revolution in traffic management and road safety, with innovation at the heart of this evolution. In this context, Visible Light Communication (VLC) emerges as a promising alternative to meet the demands for high-speed and low-latency communication. LED lamps, primarily used for lighting, can also serve as data transmission mediums. This article proposes a VLC system utilizing Wavelength Division Multiplexing (WDM) to simultaneously transmit data streams from different sources via a Free Space Optical (FSO) channel.</div><div>We evaluated the performance of this system by analyzing the impact of the Return to Zero (RZ) and Non Return to Zero (NRZ) formats at the optical transmitter on the WDM/FSO system. Simulations were conducted by varying the FSO channel distance and testing different throughput scenarios while considering weather conditions. The results show that Return to Zero, On-Off Keying (RZ-OOK) modulation can achieve high data rates at short distances, while Non Return to Zero, On-Off Keying (NRZ-OOK) modulation excels at longer distances with moderate data rates, particularly under adverse weather conditions.</div><div>These findings pave the way for innovative applications in the field of V2X communications, addressing the specific needs of both urban and non-urban environments.</div></div>","PeriodicalId":100488,"journal":{"name":"e-Prime - Advances in Electrical Engineering, Electronics and Energy","volume":"11 ","pages":"Article 100900"},"PeriodicalIF":0.0,"publicationDate":"2025-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143178610","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Optimized parameter estimation of lithium-ion batteries using an improved cuckoo search algorithm under variable temperature profile
Pub Date : 2025-01-15 DOI: 10.1016/j.prime.2025.100902
Tasadeek Hassan Dar , Satyavir Singh
Lithium-ion batteries are an intuitive choice for electric vehicles and many other gadgets. Parameters play a critical role in addressing its performance characterization. Accurate parameter estimation and real-time monitoring of lithium-ion batteries are important in modeling equivalent circuits. The characteristics of lithium-ion batteries are dynamic due to energy storage. Dynamical behavior is characterized by RC equivalent models. This work presents the estimation of parameters associated with the n-RC equivalent circuit model in integration with the Improved Cuckoo Search Algorithm (ICSA). To get it, battery tests such as HPPC test, static capacity test, and open circuit voltage test in consideration of temperatures are carried out. The experiments are carried out under different temperature ranges to record the valid data sets. ICSA is advantageous over existing algorithms in estimating the battery parameters under temperature ranges. The performance of the proposed approach captures and estimates the parameters in the dynamic range of temperatures of the lithium-ion battery. The error profile is addressed with the root mean square error and it is found to be 0.23 % at 30 °C. It is observed that experimental data with ICSA accurately matches the simulated model data at different temperature ranges.
{"title":"Optimized parameter estimation of lithium-ion batteries using an improved cuckoo search algorithm under variable temperature profile","authors":"Tasadeek Hassan Dar ,&nbsp;Satyavir Singh","doi":"10.1016/j.prime.2025.100902","DOIUrl":"10.1016/j.prime.2025.100902","url":null,"abstract":"<div><div>Lithium-ion batteries are an intuitive choice for electric vehicles and many other gadgets. Parameters play a critical role in addressing its performance characterization. Accurate parameter estimation and real-time monitoring of lithium-ion batteries are important in modeling equivalent circuits. The characteristics of lithium-ion batteries are dynamic due to energy storage. Dynamical behavior is characterized by RC equivalent models. This work presents the estimation of parameters associated with the n-RC equivalent circuit model in integration with the Improved Cuckoo Search Algorithm (ICSA). To get it, battery tests such as HPPC test, static capacity test, and open circuit voltage test in consideration of temperatures are carried out. The experiments are carried out under different temperature ranges to record the valid data sets. ICSA is advantageous over existing algorithms in estimating the battery parameters under temperature ranges. The performance of the proposed approach captures and estimates the parameters in the dynamic range of temperatures of the lithium-ion battery. The error profile is addressed with the root mean square error and it is found to be 0.23 % at 30 °C. It is observed that experimental data with ICSA accurately matches the simulated model data at different temperature ranges.</div></div>","PeriodicalId":100488,"journal":{"name":"e-Prime - Advances in Electrical Engineering, Electronics and Energy","volume":"11 ","pages":"Article 100902"},"PeriodicalIF":0.0,"publicationDate":"2025-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143178123","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A compact active planar patch antenna array for sub-6 GHz 5G applications
Pub Date : 2025-01-13 DOI: 10.1016/j.prime.2025.100903
Farid El Ghaoual , Jamal Zbitou , Mostafa Hefnawi , Aboubakr El Hammoumi
This paper presents the design, analysis, achievement, and validation of a high-performance 64-element planar patch antenna array tailored explicitly for sub-6 GHz fifth-generation (5G) communication systems. Operating at 3.5 GHz and mounted on an FR4 substrate, the antenna array exhibits a high gain of approximately 17.5 dB, with excellent input impedance matching and radiation efficiency. To further enhance the system's performance, the antenna array was integrated with a custom-designed power amplifier based on the BFP640ESD bipolar transistor. This integration enabled the achievement of an active antenna circuit, improving both transmission power and overall system efficiency. The power amplifier was designed using the Advanced Design System (ADS) solver. To ensure reliable operation, key parameters such as power efficiency, input/output impedance matching, and stability were analyzed and achieved. Integrating the power amplifier, the active antenna array was thoroughly tested into simulation and validated at 3.5 GHz. The results demonstrate that the proposed circuit not only meets the required specifications for 5G applications but also offers enhanced performance in terms of signal strength and matching input impedance across a wide bandwidth. This study confirms the benefit of incorporating an active power amplifier with a planar antenna array for modern wireless communication systems.
{"title":"A compact active planar patch antenna array for sub-6 GHz 5G applications","authors":"Farid El Ghaoual ,&nbsp;Jamal Zbitou ,&nbsp;Mostafa Hefnawi ,&nbsp;Aboubakr El Hammoumi","doi":"10.1016/j.prime.2025.100903","DOIUrl":"10.1016/j.prime.2025.100903","url":null,"abstract":"<div><div>This paper presents the design, analysis, achievement, and validation of a high-performance 64-element planar patch antenna array tailored explicitly for sub-6 GHz fifth-generation (5G) communication systems. Operating at 3.5 GHz and mounted on an FR4 substrate, the antenna array exhibits a high gain of approximately 17.5 dB, with excellent input impedance matching and radiation efficiency. To further enhance the system's performance, the antenna array was integrated with a custom-designed power amplifier based on the BFP640ESD bipolar transistor. This integration enabled the achievement of an active antenna circuit, improving both transmission power and overall system efficiency. The power amplifier was designed using the Advanced Design System (ADS) solver. To ensure reliable operation, key parameters such as power efficiency, input/output impedance matching, and stability were analyzed and achieved. Integrating the power amplifier, the active antenna array was thoroughly tested into simulation and validated at 3.5 GHz. The results demonstrate that the proposed circuit not only meets the required specifications for 5G applications but also offers enhanced performance in terms of signal strength and matching input impedance across a wide bandwidth. This study confirms the benefit of incorporating an active power amplifier with a planar antenna array for modern wireless communication systems.</div></div>","PeriodicalId":100488,"journal":{"name":"e-Prime - Advances in Electrical Engineering, Electronics and Energy","volume":"11 ","pages":"Article 100903"},"PeriodicalIF":0.0,"publicationDate":"2025-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143178609","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Accurate and optimal control of a bidirectional DC-DC converter: A robust adaptive approach enhanced by particle swarm optimization
Pub Date : 2025-01-12 DOI: 10.1016/j.prime.2025.100899
Julius Derghe Cham , Francis Lénine Djanna Koffi , Alexandre Teplaira Boum , Ambe Harrison , Paul Michael Dongmo Zemgue , Njimboh Henry Alombah
The efficient operation of DC-microgrids is highly depend on DC-DC converters. The Half-bridge Bidirectional DC-DC converter, a special class of power electronic converters has received significant attention in DC-microgrids due to its high flexibility. However, arriving at an optimal operating performance of this converter requires robust, accurate control and regulation of its output. To address the control requirements of this system, this paper proposes a robust adaptive nonlinear control strategy based on adaptive sliding mode controller. Unlike contemporary controllers, the proposed control strategy alleviates the chattering limitations of the classical sliding mode controller through the integration of a smooth hyperbolic tangent function. Additionally, the control structure is enhanced by an optimal adjustment of its gains through particle swarm optimization. A series of numerical investigations are conducted under diverse operating conditions such as variations in reference voltage, load resistance, and input voltages. The acquired results revealed a satisfactory response of the proposed control structure. Furthermore, by thoroughly comparing its performance against existing controllers such as conventional sliding mode controller, super-twisting sliding mode controller, adaptive sliding mode controller, this paper aims to emphasize the superiority of the proposed controller in achieving accurate and robust performance of the Half-bridge bidirectional DC-DC converter. Finally, experimental results were provided to validate the proposed controller in real time.
{"title":"Accurate and optimal control of a bidirectional DC-DC converter: A robust adaptive approach enhanced by particle swarm optimization","authors":"Julius Derghe Cham ,&nbsp;Francis Lénine Djanna Koffi ,&nbsp;Alexandre Teplaira Boum ,&nbsp;Ambe Harrison ,&nbsp;Paul Michael Dongmo Zemgue ,&nbsp;Njimboh Henry Alombah","doi":"10.1016/j.prime.2025.100899","DOIUrl":"10.1016/j.prime.2025.100899","url":null,"abstract":"<div><div>The efficient operation of DC-microgrids is highly depend on DC-DC converters. The Half-bridge Bidirectional DC-DC converter, a special class of power electronic converters has received significant attention in DC-microgrids due to its high flexibility. However, arriving at an optimal operating performance of this converter requires robust, accurate control and regulation of its output. To address the control requirements of this system, this paper proposes a robust adaptive nonlinear control strategy based on adaptive sliding mode controller. Unlike contemporary controllers, the proposed control strategy alleviates the chattering limitations of the classical sliding mode controller through the integration of a smooth hyperbolic tangent function. Additionally, the control structure is enhanced by an optimal adjustment of its gains through particle swarm optimization. A series of numerical investigations are conducted under diverse operating conditions such as variations in reference voltage, load resistance, and input voltages. The acquired results revealed a satisfactory response of the proposed control structure. Furthermore, by thoroughly comparing its performance against existing controllers such as conventional sliding mode controller, super-twisting sliding mode controller, adaptive sliding mode controller, this paper aims to emphasize the superiority of the proposed controller in achieving accurate and robust performance of the Half-bridge bidirectional DC-DC converter. Finally, experimental results were provided to validate the proposed controller in real time.</div></div>","PeriodicalId":100488,"journal":{"name":"e-Prime - Advances in Electrical Engineering, Electronics and Energy","volume":"11 ","pages":"Article 100899"},"PeriodicalIF":0.0,"publicationDate":"2025-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143178124","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Enhancing thyroid nodule assessment with deep learning and ultrasound imaging
Pub Date : 2025-01-12 DOI: 10.1016/j.prime.2025.100894
Jatinder Kumar , Surya Narayan Panda , Devi Dayal , Manish Sharma
The thyroid is a tiny, butterfly-shaped gland in the neck which produces hormones that are essential for controlling the body's various metabolic processes. Thyroid nodules, which are abnormal growths or lumps in the thyroid gland, are common thyroid illnesses, as are hypothyroidism, hyperthyroidism, and both. Thyroid issues are most commonly identified and categorised using thyroid ultrasonography (USG) images. They can have a range of effects on the body's metabolism and overall health. Developments in artificial intelligence (AI), particularly deep learning (DL), are helping to identify and measure patterns in clinical images because of DL's capacity towards pull out hierarchical attribute representations from images without the need for annotated images. Minimizing unnecessary fine needle aspiration (FNA) requires the essential identification of as many malignant thyroid nodules as possible, distinguishing them from benign ones. This research work introduces a technique for thyroid nodule identification in USGs, employing DL to extract relevant features. Three pre-trained DL models, namely ResNet-18, VGG-19 and AlexNet were fine-tuned before using for classification of thyroid USG images. The models' testing and training were done with Digital Database of Thyroid Ultrasound Images (DDTI) which is gold standard dataset. The results demonstrate a classification accuracy of 97.13%, 90.31% and 83.59% with ResNet-18, VGG-19 and AlexNet, respectively. The experimental findings affirm that the pre-trained network model ResNet-18 achieves superior classification performance compared to VGG-19 and AlexNet.
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引用次数: 0
Enhancing power quality in high-power renewable applications using a new extendable nine-level grid-tied converter
Pub Date : 2025-01-07 DOI: 10.1016/j.prime.2025.100898
Shivam Kumar Yadav (Member IEEE), Bhim Singh (Fellow IEEE)
This paper introduces a new multilevel converter configuration for integrating large solar plants with an 11 kV grid tailored for a megawatt scale. This configuration employs twelve switches with a symmetrical progression, resulting in nine levels in phase voltage. Consisting of main power modules (MPM) and extension power modules(EPMs), this modular system effectively manages solar power. This paper elucidates various states and operational modes, highlighting each level's flawless performance and emphasizing configuration's scalability to accommodate additional power modules. The discussion initiates with a comprehensive exploration of the converter's operation, followed by its grid-tied fundamental control. Test cases are presented to assess system's performance in varying solar conditions. Converter employs polynomial-based selective harmonics elimination (SHE) to switch at fundamental frequency, ensuring efficiency in steady-state and dynamic conditions. Finally, new solar converter undergoes rigorous testing in Simulink, highlighting its superior dynamics for grid-tied operations. Moreover, simulated results are validated in a laboratory real-time test bench.
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引用次数: 0
SDRG-Net: Integrating multi-level color transformation encryption and ICNN-IRDO feature analysis for robust diabetic retinopathy diagnosis
Pub Date : 2025-01-06 DOI: 10.1016/j.prime.2025.100895
Venkata Kotam Raju Poranki, B. Srinivasarao
The Internet of Medical Things (IoMT) has emerged as a potential solution to various challenges in disease grading, offering enhanced communication between patients and doctors and providing more robust guidance for disease management. Diabetic Retinopathy (DR) grading is crucial for the timely diagnosis and treatment of this common complication of diabetes, which can lead to blindness if left untreated. Existing methods for DR grading often need more accuracy and efficiency due to challenges such as variations in image quality, subtle lesion features, and imbalanced datasets. Furthermore, existing DR grading methods have exhibited lower security properties due to the need for image encryption algorithms in the IoMT environment. A Secure DR Grading Network (SDRG-Net) is proposed to address these issues, integrating several advanced techniques. Firstly, preprocessing techniques are applied to normalize the EyePACS and Messidor datasets and prepare the images for subsequent analysis. Next, Multi Level Color Transformation (MLCT) based image encryption is employed to enhance the robustness and security of the data, ensuring patient privacy while maintaining diagnostic accuracy. The encrypted images are then fed into an Iterative Convolutional Neural Network (ICNN) architecture for feature extraction, leveraging deep learning capabilities to learn discriminative features from the retinal images automatically. This step enables the model to capture intricate patterns and abnormalities indicative of DR. Furthermore precisely, an Improved Red Deer Optimization (IRDO) algorithm is introduced for feature selection, which iteratively refines the feature space to retain the most informative features while discarding redundant or noisy ones. This enhances the efficiency and interpretability of the model, leading to improved performance in DR grading. Finally, a Bagging classifier is employed for classification, leveraging ensemble learning to combine multiple base classifiers trained on different subsets of the data. Finally, the proposed SDRG-Net achieves high performance with an accuracy of 99.65 % on the EyePACS dataset and 99.14 % on the Messidor dataset, demonstrating its robustness and effectiveness in DR grading.
{"title":"SDRG-Net: Integrating multi-level color transformation encryption and ICNN-IRDO feature analysis for robust diabetic retinopathy diagnosis","authors":"Venkata Kotam Raju Poranki,&nbsp;B. Srinivasarao","doi":"10.1016/j.prime.2025.100895","DOIUrl":"10.1016/j.prime.2025.100895","url":null,"abstract":"<div><div>The Internet of Medical Things (IoMT) has emerged as a potential solution to various challenges in disease grading, offering enhanced communication between patients and doctors and providing more robust guidance for disease management. Diabetic Retinopathy (DR) grading is crucial for the timely diagnosis and treatment of this common complication of diabetes, which can lead to blindness if left untreated. Existing methods for DR grading often need more accuracy and efficiency due to challenges such as variations in image quality, subtle lesion features, and imbalanced datasets. Furthermore, existing DR grading methods have exhibited lower security properties due to the need for image encryption algorithms in the IoMT environment. A Secure DR Grading Network (SDRG-Net) is proposed to address these issues, integrating several advanced techniques. Firstly, preprocessing techniques are applied to normalize the EyePACS and Messidor datasets and prepare the images for subsequent analysis. Next, Multi Level Color Transformation (MLCT) based image encryption is employed to enhance the robustness and security of the data, ensuring patient privacy while maintaining diagnostic accuracy. The encrypted images are then fed into an Iterative Convolutional Neural Network (ICNN) architecture for feature extraction, leveraging deep learning capabilities to learn discriminative features from the retinal images automatically. This step enables the model to capture intricate patterns and abnormalities indicative of DR. Furthermore precisely, an Improved Red Deer Optimization (IRDO) algorithm is introduced for feature selection, which iteratively refines the feature space to retain the most informative features while discarding redundant or noisy ones. This enhances the efficiency and interpretability of the model, leading to improved performance in DR grading. Finally, a Bagging classifier is employed for classification, leveraging ensemble learning to combine multiple base classifiers trained on different subsets of the data. Finally, the proposed SDRG-Net achieves high performance with an accuracy of 99.65 % on the EyePACS dataset and 99.14 % on the Messidor dataset, demonstrating its robustness and effectiveness in DR grading.</div></div>","PeriodicalId":100488,"journal":{"name":"e-Prime - Advances in Electrical Engineering, Electronics and Energy","volume":"11 ","pages":"Article 100895"},"PeriodicalIF":0.0,"publicationDate":"2025-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143178127","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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e-Prime - Advances in Electrical Engineering, Electronics and Energy
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